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Investigating Scientific Claims

Investigating Scientific Claims. Outline. I. Experimental vs. Observational Science II. Evidence vs. Inference A. Definitions B. Examples III. Types of Errors A. Random B. Systematic IV. Critical Thinking A. Definition B. Methods. Experimental vs. Observational Science.

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Investigating Scientific Claims

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  1. Investigating Scientific Claims

  2. Outline I. Experimental vs. Observational Science II. Evidence vs. Inference A. Definitions B. Examples III. Types of Errors A. Random B. Systematic IV. Critical Thinking A. Definition B. Methods

  3. Experimental vs. Observational Science • Experimental: based on direct manipulation of the independent variables. (polar bear example from last week) • Observational: based on selecting existing cases with different values for the independent variables. E.g. thalidomide babies from the fifties-look at adults, those whose mom’s took vs. didn’t take • Historical investigations must be observational • Current investigations may be either

  4. Evidence • Must be a fact or measurement about something that has actually occurred • Information attributed to an identified scientific source • Specific scientist • Scientific organization • Scientific journal

  5. Examples of Evidence • Skelly (1997) found that in the presence of predators, tadpoles (Pseudacris spp.) were less than half as active as control tadpoles (no predator present). • Skelly (1997) also found growth rates of more stationary tadpoles dropped • Smith et. al. found a decline in a Brazilian bird species • Smith et. al. also found 30% of Brazilian rainforest has declined

  6. Inference • Interpretation of data • Conclusion made based on the given facts but not specifically tested

  7. Examples of Inference • Taken together, the results of Skelly’s (1997) experiments suggest Pseudacris spp. tadpoles have a behavioral trade-off between growth and risk of predation • Decrease in Brazilian bird species is due to rain forest decline

  8. Types of Errors • Random Error: errors in measurement that vary randomly from one measurement to the next. • May be due to person making the measurement • May be due to variations in the equipment • Systematic Error: errors that have a consistent bias • May be due to mistakes in setting up or making the measurement • Equipment not calibrated properly

  9. Minimizing Error • Random error may be minimized by making many measurements and averaging the results • Systematic error can NOT be minimized by increasing #of measurements or by averaging measurements

  10. Critical Thinking • Actively and skillfully evaluating information gathered from observation and experience and using that insight to form conclusions that guide your beliefs and actions • Self-directed, self-disciplined, self-monitored, and self-corrective thinking

  11. Methods of Critical Thinking • Identify and evaluate premises and conclusions in an argument • Analyze inferences based on evidence, those based on value judgments • Assign weight to opposing viewpoints based on chains of reasoning, sources of information (reliability) • Adjust weighting depending on relevance to central issue, lack of specific evidence or contradictions

  12. Rules for conditionally accepting a claim • Conditionally accept claim if it is well supported by evidence cited in article • Claim is published in reputable journal, work done by reputable scientists • No evidence in article has contradicted claim • Do not accept if there is insufficient evidence

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